Time to Accept It: publishing in the Journal of Statistical Software

When I was considering submitting my paper on psd to J. Stat. Soft. (JSS), I kept noticing that the time from “Submitted” to “Accepted” was nearly two years in many cases.  I ultimately decided that was much too long of a review process, no matter what the impact factor might be (and in two years time, would I even care?).  Tonight I had the sudden urge to put together a dataset of times to publication.

Fortunately the JSS website is structured such that it only took a few minutes playing with XML scraping (*shudder*) to write the (R) code to reproduce the full dataset.  I then ran a changepoint (published in JSS!) analysis to see when shifts in mean time have occurred.  Here are the results:


Top: The number of days for a paper to go from 'Submitted' to 'Accepted'.  Middle: In log2(time), with lines for one month, one year, and two years. Bottom frame: changepoint analyses.
Top: The number of days for a paper to go from ‘Submitted’ to ‘Accepted’ as a function of the cumulative issue index (each paper is an “issue” in JSS).
Middle: In log2(time), with lines for one month, one year, and two years.
Bottom frame: changepoint analyses.

Pretty interesting stuff, but kind of depressing: the average time it takes to publish is about 1.5 years, with a standard deviation of 206 days.  There are many cases where the paper review is <1 year, but those tend to be in the ‘past’ (prior to volume 45, issue 1).

Of course, these results largely reflect an increase in academic impact (JSS is becoming more impactful), which simultaneously increases the number of submissions for the editors to deal with.  So, these data should be normalized by something.  By what, exactly, I don’t know.

And, finally, I can’t imagine how the authors of the paper that went through a 1400+ day review process felt — or are they still feeling the sting?

Here’s my session info:

R version 3.1.0 (2014-04-10)
Platform: x86_64-apple-darwin13.1.0 (64-bit)

[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats graphics grDevices utils datasets methods base

other attached packages:
[1] changepoint_1.1.5 zoo_1.7-11 plyr_1.8.1 XML_3.98-1.1

loaded via a namespace (and not attached):
[1] grid_3.1.0 lattice_0.20-29 Rcpp_0.11.1 tools_3.1.0
And here's the R-code needed to reproduce the dataset and figure:

#Current Volume:
cvol <- 58
# set to 'TRUE' if you want to
# reproduce the dataset with each
# run (not recommended)
redo <- FALSE

jstat.xml <- function(vol=1, tolist=TRUE){
 src <- "http://www.jstatsoft.org/"
 vsrc <- sprintf("%sv%i",src,vol)
 X <- xmlParse(vsrc)
 if (tolist) X <- xmlToList(X)

jstat.DTP <- function(vol=1, no.authors=FALSE, no.title=FALSE){
 # Get article data
 xl <- jstat.xml(vol)
 Artic <- xl$body[[4]]$div$ul # article data

 # Vol,Issue
 issues <- ldply(Artic, function(x) return(x[[5]][[1]]))$V1
 issues2 <- ldply(strsplit(issues,split=","),
 .fun=function(x){gsub("\n Vol. ","",gsub("Issue ","",x))})

 # Accepted
 dates <- ldply(Artic, function(x) return(x[[6]][[1]]))$V1
 dates2 <- ldply(strsplit(dates, split=","),
 .fun=function(x){as.Date(gsub("Accepted ","",gsub("Submitted ","",x)))})

 Dat <- data.frame(Volume=issues2$V1, Issue=issues2$V2, Date=issues2$V3,
 Submitted=dates2$V1, Accepted=dates2$V2,
 Days.to.pub=as.numeric(difftime(dates2$V2, dates2$V1, units="days")),
 Author=NA, Title=NA)

 if (!no.authors){
 # Authors
 Dat$Author <- ldply(Artic, function(x) return(x[[3]][[1]]))$V1

 if (!no.title){
 # Title
 Dat$Title <- ldply(Artic, function(x) return(x[[1]][[1]]))$V1


# Shakedown
#ldply(57:58, jstat.DTP)

if (!exists("Alldata") | redo){
 Alldata <- ldply(seq_len(cvol), jstat.DTP)
 save(Alldata, file="JStatSoft_DtP.rda")
} else {

Alldata.s <- arrange(Alldata, Days.to.pub)
Cpt <- suppressWarnings(cpt.mean(Alldata$Days.to.pub, method="SegNeigh", Q=4))
niss <- length(Cpt@data.set)


PLT <- function(){
 par(las=1, cex=0.8)

 with(Alldata, {
 xlim=c(0,niss), #xaxs="i",
 type="l", col="grey", ylab="Days", xaxt="n",
 points(Days.to.pub, pch=3)
 mtext("Time to 'Accepted': J. Stat. Soft.", font=2, line=0.5)
 axis(1, labels=FALSE)
 xlim=c(0,niss), #xaxs="i",
 pch=3, ylab="log2 Days")
 yt <- log2(356*c(1/12,1:2))
 abline(h=yt, col="red", lty=2)

 xlim=c(0,niss), #xaxs="i",
 xlab="Issue index", ylab="Days",
 mtext("Changes in mean", font=2, line=-2, adj=0.1, cex=0.8)

 Dm <- lbls <- round(param.est(Cpt)$mean)
 lbls[1] <- paste("section mean:",lbls[1])
 Lc <- cpts(Cpt)
 yt <- -75-max(Dm)+Dm
 xt <- c(0,Lc)+diff(c(0,Lc,niss))/2

 text(xt, yt, lbls, col="red", cex=0.9)


6 thoughts on “Time to Accept It: publishing in the Journal of Statistical Software

  1. did not work on my Windows computer
    Entity ‘mdash’ not defined
    Entity ‘nbsp’ not defined

    > Cpt niss
    > summary(Cpt)
    Error in summary(Cpt) : object ‘Cpt’ not found

    Probably my fault, but thought u would like to know

  2. Thanks, but I’m not sure how to help without a bit more info (the code works, as published, on my system). Those “Entity” messages should only be warnings, but maybe it’s different for Windows?? The changepoint analysis will of course fail if the dataset hasn’t been assembled.

    Perhaps try updating the XML, plyr, and changepoint packages?

  3. And I just noticed that my paper (http://www.jstatsoft.org/v49/i08/) has incorrect time data. it was published mid-2012, and submitted feb-1-2010, though JSS claims that it was submitted a whole year after it actually was! For those counting, that is 852 days between submission and publication. And yes, it does leave a sting 🙂

    The editors actually lost the paper for 6 months, and didn’t even send it out for peer reviews until 6-9 months after I submitted it. Since it was actively developed software, the paper became woefully out of date twice during the publication process.

    1. Ouch! The out-of-date effect you mention seems inevitable with such long lag times.

      Also, I’m fairly sure a number of those points are inaccurate. Some even have zero days between submission and acceptance, which seems highly plausible (p < 0.05) 🙂

      Thanks for the insight, Ian.

  4. JSS practices some “tactics” (maybe it isn’t intentional) to reduce time to acceptance. Once of those being that if you get a reject and resubmit, you get a new submission number and your time to acceptance restarts. Thus I suspect there are several papers (changepoint being one) that have much longer times than indicated.
    This also doesn’t take into account the time taken for those papers which were rejected. Should be shorter as it is likely to be 1 review round but would provide a fuller picture.

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